Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods

The therapeutic approach of targeted protein degradation(TPD)is gaining momentum due to its potentially superior effects comparedwith protein inhibition. Recent advancements in the biotech and pharmaceuticalsectors have led to the development of compounds that are currentlyin human trials, with some showing promising clinical results. However,the use of computational tools in TPD is still limited, as it hasdistinct characteristics compared with traditional computational drugdesign methods. TPD involves creating a ternary structure (protein-degrader-ligase)responsible for the biological function, such as ubiquitination andsubsequent proteasomal degradation, which depends on the spatial orientationof the protein of interest (POI) relative to E2-loaded ubiquitin.Modeling this structure necessitates a unique blend of tools initiallydeveloped for small molecules (e.g., docking) and biologics (e.g.,protein-protein interaction modeling). Additionally, degradermolecules, particularly heterobifunctional degraders, are generallylarger than conventional small molecule drugs, leading to challengesin determining drug-like properties like solubility and permeability.Furthermore, the catalytic nature of TPD makes occupancy-based modelinginsufficient. TPD consists of multiple interconnected yet distinctsteps, such as POI binding, E3 ligase binding, ternary structure interactions,ubiquitination, and degradation, along with traditional small moleculeproperties. A comprehensive set of tools is needed to address thedynamic nature of the induced proximity ternary complex and its implicationsfor ubiquitination. In this Perspective, we discuss the current stateof computational tools for TPD. We start by describing the seriesof steps involved in the degradation process and the experimentalmethods used to characterize them. Then, we delve into a detailedanalysis of the computational tools employed in TPD. We also presentan integrative approach that has proven successful for degrader designand its impact on project decisions. Finally, we examine the futureprospects of computational methods in TPD and the areas with the greatestpotential for impact.